Building Data Lakes on AWS

Building Data Lakes on AWS

This course is part of AWS Cloud Solutions Architect Professional Certificate

Instructors: Rafael Lopes

Access provided by SGCSRC

40,024 already enrolled

6 modules

Gain insight into a topic and learn the fundamentals.

308 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

92%

Most learners liked this course

6 modules

Gain insight into a topic and learn the fundamentals.

308 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

92%

Most learners liked this course

What you'll learn

Apply data lake methodologies in planning and designing a data lake.
Describe the components and services required for building an AWS data lake.
Compare the ways data can be ingested, stored, and transformed in a data lake.
Explain how to secure a data lake with appropriate permissions.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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Build your Data Analysis expertise

This course is part of the AWS Cloud Solutions Architect Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Amazon Web Services

There are 6 modules in this course

The fundamental-level course is typically designed for individuals with a basic understanding of data storage and processing concepts but little to no prior experience with building data lakes on AWS specifically. After a brief introduction to Data Lakes, we'll introduce data ingestion, cataloging and preparation, concluding with an overview of querying data with Amazon Athena. The course will continue with an AWS Lake Formation overview, including a hands-on lab where you'll build a data lake. We'll then introduce data processing and analytics leveraing AWS Glue before diving into automated data lake creatiokn using Lake Formation blueprints. Finally, we'll close with Modern Data Architectures on AWS with a lab that covers publishing and consuming data products as a service.

This module provides an overview of data lakes, their purpose, and how they differ from data warehouses. It also covers the components and architectures involved in data lakes.

What's included

5 videos1 reading2 assignments1 plugin

5 videos Total 19 minutes

Course Introduction and Overview 3 minutes
Module Objectives 1 minute
Why Data Lakes? 4 minutes
Data Lake vs Data Warehouse 5 minutes
Components and Architectures 6 minutes

1 reading Total 2 minutes

Pre-Course Survey 2 minutes

2 assignments Total 60 minutes

Knowledge Check 30 minutes
Pre-Assessment 30 minutes

1 plugin Total 15 minutes

Pre-Course Survey 15 minutes

This module focuses on the processes of ingesting data into a data lake, cataloging the data, and preparing it for analysis. It covers topics such as data lake storage, data ingestion methods, crawling and cataloging data, data formatting, partitioning, compression, and querying data with Amazon Athena.

What's included

10 videos1 reading1 assignment1 plugin

10 videos Total 46 minutes

Module Objectives 1 minute
Data Lake Storage 5 minutes
Data Ingestion 7 minutes
Crawl and Catalog Data 4 minutes
Demo: Creating and Running a Glue Crawler 9 minutes
Formatting the Data in the Lake 3 minutes
Partitioning, Compressing, and Compacting the Data in the Lake 4 minutes
Query Data with Amazon Athena 3 minutes
Demo: Querying CSV data with Amazon Athena 3 minutes
Demo: Columnar data formats with Amazon Athena - a performance and cost comparison 7 minutes

1 reading Total 2 minutes

Mid-Course Survey 2 minutes

1 assignment Total 30 minutes

Knowledge Check 30 minutes

1 plugin Total 15 minutes

Mid-Course Survey 15 minutes

This module introduces AWS Lake Formation, a service that helps build and manage data lakes on AWS. It covers the basic permission model, and provides an overview of the service’s features and capabilities.

What's included

3 videos1 reading1 assignment1 app item

This module covers data transformation techniques and tools like AWS Glue for processing and analyzing data in the data lake. It includes hands-on demos and a technical talk on Glue and Athena Federated Queries.

What's included

7 videos1 assignment1 discussion prompt

7 videos Total 37 minutes

Module Objectives 1 minute
Data Transformation 4 minutes
Data Processing with AWS Glue 5 minutes
AWS Glue Jobs and Workflows 3 minutes
Demo - Glue Databrew 9 minutes
Demo - Glue Studio 9 minutes
Tech Talk - Glue / Athena Federated Queries 7 minutes

1 assignment Total 30 minutes

Knowledge Check 30 minutes

1 discussion prompt Total 10 minutes

AWS Glue 10 minutes

This module explores advanced features and configurations of AWS Lake Formation, including blueprints, workflows, and fine-grained access control. It also covers data visualization with Amazon QuickSight.

What's included

5 videos1 assignment1 app item

5 videos Total 21 minutes

Module Objectives 1 minute
Using Blueprints and Workflows 3 minutes
Fine-grained Access Control 6 minutes
Demo - LF-Tags 7 minutes
Visualizing Data with QuickSight - Demo 4 minutes

1 assignment Total 30 minutes

Knowledge Check 30 minutes

1 app item Total 60 minutes

Lab 2: Automate Data Lake Creation Using AWS Lake Formation Blueprints 60 minutes

This module introduces the concept of modern data architecture and its implementation on AWS. It covers data movement scenarios, data sharing models, and relevant readings.